Optimization

Webster's definition: To make most favorable or best possible for a
certain purpose, or under certain conditions.

Teddy Roosevelt incorporated optimization into his personal credo,
providing the famous quote, "Do what you can, with what you have, where
you are."

This seems straightforward enough -- we just take whatever resources are
available, use them as efficiently and effectively as possible, to
produce the best possible outcome. But in the LML setting, this can be
difficult for many reasons. In this article we will explore some of the
more salient challenges and how they can be turned to competitive
advantage.

Perspective: For whom are we optimizing?

At first glance, the answer to this may seem obvious -- we are
optimizing for OUR benefit, to improve OUR profits and OUR market share,
etc. And this is certainly true, whether directly or indirectly. But
in the LML, the strategies and tactics for achieving these goals vary
depending on the role your company plays. For example, a
shipper/importer may be focused on reducing transportation cost per unit
of product, while his intermediate service provider (forwarder/broker)
is trying to increase revenue and yields, and the carrier is concerned
with return on assets. At face value these objectives are in direct
conflict with one another, making optimization less straightforward than
it first appeared.

There is no single answer to the question, "for whom are we optimizing?"
In fact, the real answer is that we want to optimize for all parties
simultaneously -- but those who seek long term competitive advantage
will focus on the shipper/importer's needs first. Why?
Because theirs is the first procurement dollar spent in the LML model.
That dollar is then spent by the intermediary to procure vessel space
and then by the asset based carrier to procure vessel capacity -- a
classic demand chain. And as we learned last issue, the procurement
function is the strategic componenent of the LML.

A simple case

In the above example, the shipper/importer seeks to reduce transit time
and increase load factor. If that optimization strategy is successful,
the short term savings will come directly out of the pocket of the
intermediary as volumes from that customer drop. Many service providers
choose to focus short term on this built-in disincentive, cooperating in
shipper optimization solutions reluctantly or not at all. But the more
savvy players take a longer view -- always keeping in mind that the LML
is a cycle that will enable them to leverage their performance on behalf
of their customer to competitive advantage in the next round, and the
next, etc.

For example, the intermediary might enter a gain-sharing arrangement
with the shipper to enjoy some of the optimization benefits. While this
will not be dollar for dollar, the impact will be significant on the net
revenue line because there is no off-setting cost of transportation.
The greater benefit over time for the intermediary will be in customer
retention and increased market share as more shippers procure their
services in order to reap similar benefits.

Scope: What are we optimizing?

Keeping the perspective issue in mind, we will examine this question
primarily from the shipper/importer's point of view. As with the
previous question, there is no single answer on what to optimize. But
all optimization efforts will focus on any combination of these three
general components:

Time

Money

Quality

The supply chain requirements of the shipper/importer's particular
industry will determine which of these three areas to emphasize, but all
must be considered. At the most general level, optimization means
finding the best possible balance between the three elements in order to
achieve business objectives, be they profitability, market share, return
on assets, shorter cash to cash cycle, etc.

In the LML construct, this means we could be optimizing one or several
of these key performance areas:

Inventory levels

Average transit time duration

Transit time variability

Transportation cost per unit

Warehousing/postponement cost per unit

Outsourcing strategies

Facility locations

Sourcing decisions

Capacity

Order fulfillment

Claims

Returns

Billing timeliness and accuracy

A deeper look into optimizing each of the above is outside the scope of
this artical and whole libraries have been written on the subject. For
now, it is important to understand that a sound optimization initiative
requires a clearly defined scope that is in line with business
objectives.

Caution: One must bear in mind the inherent trade offs between many of
the performance areas. Otherwise, it is easy to sub-optimize that which
is IN SCOPE at the expense of that which is OUT OF SCOPE. For instance,
100% order fulfillment rates are easily attained if no consideration is
given to inventory levels. Early recognition of these trade-offs will
help ensure that the proper controls and measures are in place to
prevent such "collateral damage." While looking at these trade-offs it
is important to look at employee incentive compensation models to ensure
that they are not rewarding sub-optimal agendas.

Time: That perfectly limited resource

If time were no issue, optimizing almost anything would be a trivial
matter. But in the ever accelerating business world, it has become our
most valuable commodity (even in the face of soaring fuel prices).
Goods move faster, the same dollar is spent and respent dozens of times
on three continents in the time it used to take to spend it once, and
customers have come to expect high goods availability in short delivery
times.

Accelerated supply chain processes and transaction cycles force business
leaders to make decisions more quickly and with less information than
would be the case if they had more time. Paradoxically, this time
crunch puts a higher premium on optimization while at the same time
making it more difficult to achieve.

In our last issue on Procurement, we mentioned that the ideal time to
optimize is at the point where procurement decisions are made. But
limited time and information make this virtually impossible. However,
the principle still stands -- the earlier in the LML optimization takes
place, the more benefits to be derived in the remainder of the cycle.
This principle should be a key driver in optimization strategies.

Information: The foundation of optimization

All optimization starts with timely and accurate information from which
analyses can be developed. An axiom of 6 Sigma quality teaching says,
"If you can't measure it, you can't improve it." Much of the required
information is related to the key performance areas listed in the Scope
section above. Notice that some of the information is related to cost,
while the balance deals with performance and execution. This is an
important distinction because both types of information are required for
optimization, but they are gathered in very different ways.

As just shown, time limitations make it increasingly difficult to
collect quality information to be properly anaylzed in support of sound
decisions. Since time is perfectly limited, we must turn to our methods
of gathering and analyzing information in order to fundamentally improve
optimization benefits.

Fortunately, much of this information is generated through day to day
planning and transactional activities -- especially the cost related
information. The performance and execution information is not created
naturally through the accounting process, so other systems must be
employed to close the gap.

The challenge is to harness the information in a way that enables
analysis and decision making virtually on-demand. This may sound "pie
in the sky," but many companies have invested aggregate billions of
dollars into ERP and data-warehousing solutions in search of such
capability within the four walls of their enterprises. The problem is
that these systems have a large "blind spot" when it comes to
transportation and logistics activities beyond those four walls.

However, there are IT solutions available that make LML optimization
with real time information and on-demand analysis & decision support
viable.

Conclusion: How do we Optimize?

The short answer is by overcoming the four key challenge areas covered
above. More specifically, the first two relatively simple once we are
aware of them:

But the last two -- Time and Information -- are not so easy. These
require IT strategies and tools that complement and overcome the LML
blind spots of ERP systems, while at the same time interfacing with
these systems to share information.

There are now internet native solutions available that enable on-demand
optimization from real-time information. Ideally, such a system will:

integrate Optimization into the strategic Procurement process

have execution and service performance measurement capabilities to
ensure real time availability of information related to these activities

be web-services enabled to maximize ERP and other system interfacing
opportunities

be scalable and configurable to your specific requirements, rather
than requiring wholesale business process changes

While optimization seems an elusive goal given all of the challenges,
the fact is that the tools are now available to make it a reality.
Those who employ such tools -- especially to optimize procurement
decisions -- will enjoy a competitive advantage throughout the entire
Logistics Management Lifecycle.